Omics data is not leveraged effectively in the biotechnology industry due to lack of tools to rapidly access public and private data and to design cellular manipulations or interventions based on the data. With this project we aim to make a broad spectrum of omics data useful to the biotechnology industry covering application areas ranging from industrial biotechnology to human health. We will develop novel approaches for integrative model-based omics data analysis to enable 1) Identification of novel enzymes and pathways by mining metagenomic data, 2) Data-driven design of cell factories for the production of chemicals and proteins, and 3) Analysis and design of microbial communities relevant to human health, industrial biotechnology and agriculture. All research efforts will be integrated in an interactive web-based platform that will be available for the industrial and academic research and development communities, in particular enhancing the competitiveness of biotech SMEs by economizing resources and reducing time-to-market within their respective focus areas. The platform will be composed of standardized and interoperable components that service-oriented bioinformatics SMEs involved in the project can reuse in their own products. An important aspect of the platform will be implementation of different access levels to data and software tools allowing controlling access to proprietary data and analysis tools. Two end-user companies will be involved in practical testing of the platform built within the project using proprietary omics data generated at the companies.

METACARDIS applies a systems medicine multilevel approach to identify biological relationships between gut microbiota, assessed by metagenomics, and host genome expression regulation, which will improve understanding and innovative care of cardiometabolic diseases (CMD) and their comorbidities. CMD comprise metabolic (obesity, diabetes) and heart diseases characterized by a chronic evolution in ageing populations and costly treatments. Therapies require novel integrated approaches taking into account CMD natural evolution.
METACARDIS associates European leaders in metagenomics, who have been successful in establishing the structure of the human microbiome as part of the EU FP7 MetaHIT consortium, clinical and fundamental researchers, SME, patients associations and food companies to improve the understanding of pathophysiological mechanisms, prognosis and diagnosis of CMD.
We will use next-generation sequencing technologies and high throughput metabolomic platforms to identify gut microbiota- and metabolomic-derived biomarkers and targets associated with CMD risks. The pathophysiological role of these markers will be tested in both preclinical models and replication cohorts allowing the study of CMD progression in patients collected in three European clinical centres of excellence. Their impact on host gene transcription will be characterised in patients selected for typical features of CMD evolution. Application of computational models and visualisation tools to complex datasets combining clinical information, environmental patterns and gut microbiome, metabolome and transcriptome data is a central integrating component in the research, which will be driven by world leaders in metagenomic and functional genomic data analysis. These studies will identify novel molecular targets, biomarkers and predictors of CMD progression, paving the way for personalized medicine in CMD.

Cancer is a complex disease involving multiple genetic and epigenetic events occurring, and influencing each other, over a long period of time. Understanding cancer, and ultimately developing effective targeted therapies, will therefore require that mutations and epigenetic alterations be systematically investigated during the multiple stages of disease development, from identifiable pre-neoplastic phases to overt cancer. Until now, no systematic effort has been undertaken to investigate these multiple layers of genome organization and function during cancer development. MODHEP aims at providing a 360 understanding of liver cancer, one of the most common types of tumors and, because of the homogeneity of the hepatic tissue, the most experimentally tractable one. The consortium brings together elite European scientists in the fields of genetics, chromatin regulation, genomics, liver cancer, computational and systems biology. This combination of skills will allow us to investigate and model at unprecedented resolution the chain of events leading from environmental perturbations and the occurrence of driver mutations to preneoplastic disease and cancer. Our experimental plan reflects some grounded assumptions: 1. cancer cannot be modeled without detailed information on the preneoplastic stages of disease; 2. genetic heterogeneity in humans would make systems-level modeling non realistic from a practical point of view. Both of these limitations are bypassed by the use of well-defined mouse models, followed by evaluation of the main conclusions in clinical samples; 3. many early stage driving events in cancer represent epigenetic alterations, which are invisible to classical genetic analysis, and are confounded by secondary and tertiary events in established tumors. Our approach will enable the identification of therapeutically relevant early-stage genetic and epigenetic alterations and the definition of their interplay in tumor development and maintenance.

The main objective of this research proposal is to identify and elaborate those characteristics of ENM that determine their biological hazard potential. This potential includes the ability of ENM to induce damage at the cellular, tissue, or organism levels by interacting with cellular structures leading to impairment of key cellular functions. These adverse effects may be mediated by ENM-induced alterations in gene expression and translation, but may involve also epigenetic transformation of genetic functions. We believe that it will be possible to create a set of biomarkers of ENM toxicity that are relevant in assessing and predicting the safety and toxicity of ENM across species. The ENM-organism interaction is complex and depends, not simply on the composition of ENM core, but particularly on its physico-chemical properties. In fact, important physico-chemical properties are largely governed by their surface properties. All of these factors determine the binding of different biomolecules on the surface of the ENM, the formation of a corona around the ENM core. Thus, any positive or negative biological effect of ENM in organisms may be dynamically modulated by the bio-molecule corona associated with or substituted into the ENM surface rather than the ENM on its own. The bio-molecule corona of seemingly identical ENM cores may undergo dynamic changes during their passage through different biological compartments; in other words, their biological effects are governed by this complex surface chemistry. We propose that understanding the fundamental characteristics of ENM underpinning their biological effects will provide a sound foundation with which to classify ENM according to their safety. Therefore, the overarching objective of this research is to provide a means to develop a safety classification of ENM based on an understanding of their interactions with living organisms at the molecular, cellular, and organism levels based on their material characteristics.

Phosphorylation is the most widely studied posttranslational modification occurring in cells. While mass spectrometry-based proteomics experiments are uncovering thousands of novel in vivo phosphorylation sites, the identification of kinase specificity rules still remains a relatively slow and often inefficacious task. In the last twenty years, many efforts have being devoted to the experimental and computational identification of sequence and structural motifs encoding kinase-substrate interaction key residues and the phosphorylated amino acid itself. In this review, we retrace the road to the discovery of phosphorylation sequence motifs, examine the progresses achieved in the detection of three-dimensional motifs and discuss their importance in the understanding of regulation and de-regulation of many cellular processes.